Emperical Modeling of Econometric Data

• Substance Abuse
• Labor Productivity

Acceletrated Life and Degradation Testing

• Prediction Intervals
• Shelf Life

Prediuction Intervals,Unit Root and Long Memory Processes, Volatility Modeling

• Asymptotics
• The Seive Bootstrap
• Unit Root Tests
• Modeling Stochastic Volatility
• Modeling Electricity Spot Prices and Demand
• Count Data Time Series

Statistical Applications in:

• Biology
• Environmental Engineering & Science
• Industrial Engineering
• Matrials Science
• Psychology
• Social Sciences
• Transportation Engineering

Publications in Last Ten Years

Archival Journals

Zhang, Yi., Samaranayake, VA., Olbricht, GR., Thimgan, M. Predicting Lifespan of Drosophila Melanogaster: A Novel Application of Convolutional Neural Networks and Zero-Inflated Autoregressive Conditional Poisson Model.Stat. 2020. – In press.

Krishnan, R., Garg, S., Jagannathan, S., and Samaranayake, VA. Distributed Learning of Deep Sparse Neural Networks for High-dimensional Classification. IEEE Transactions on Neural Networks and Learning Systems. 2020. – Accepted for publication.

Jornaz, A. and Samaranayake, VA. A Multi-Step Approach to Modeling the 24-hour Daily Profiles of Electricity Load using Daily Splines, Energies, 2019, 12(21), 4169; https://doi.org/10.3390/en12214169.

Krishnan,R,  Samaranayake, VA, Jagannathan, S. A Hierarchical Dimension Reduction Approach for Big Data with Application to Fault Diagnostics, Big data research. 2019, 18. https://doi.org/10.1016/j.bdr.2019.100121.

Krishnan, R, Jagannathan, S, Samaranayake, VA. Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata, IEEE Transactions on Neural Network and Learning Systems, Print ISSN: 2162-237X, https://doi.org/10.1007/978-3-030-31764-5\_1.

Krishnan, R, Samaranayake, VA, Jagannathan, S. A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Big Data, IEEE Transactions on Knowledge and Data Engineering, 31(12), 2249-2018, DOI: 10.1109/TKDE.2018.2876848.
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8496836&isnumber=4358933.

J Lisse, C Fiebelman, L Wang, N Ercal, V Samaranayake, G Olbricht, M Thimgan; 0037 Molecular Markers Of Biological Aging In Predicted Short-lived Flies, Sleep, 41, Issue suppl_1, 2018, A15, https://doi.org/10.1093/sleep/zsy061.036.

Ray, CS, Samaranayake, V.A. Mohammadkhah, A, Day, TE,  Day, DE.  Iron phosphate glass waste forms for vitrifying Hanford AZ102 Low Activity Waste (LAW), part II: Property-composition model. Journal of Non-Crystalline Solids. 2018. 495, 107-116.  https://doi.org/10.1016/j.jnoncrysol.2018.05.007.

Meng, W, Samaranayake, VA, Khayat, K. Factorial Design and Optimization of Ultra-High-Performance Concrete with Lightweight Sand. 2018. ACI Materials Journal. 2018; 115(1), 129-138.

Wagner-Muns, IM, Guardiola, IG, Samaranayake, VA, Kayani, WI. A Functional Data Analysis Approach to Traffic Volume Forecasting. IEEE Transactions on Intelligent Transport Systems. , 2018; 19(3), 878-888.

Wilson, JL., Samaranayake, VA, Limmer, MA, Burken, J. Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion. 2018, PLoS ONE 13(2): e0193247. https://doi.org/10.1371/journal.pone.0193247.

Bham,  GH., Manepalli, URR,  and Samaranayake, VA.  A  Composite  Rank  Measure Based on Principal Component Analysis for Hotspot  Identification on Highways. Journal of Transportation Safety and Security, 2017. DOI: 10.1080/19439962.2017.1384417, 2017.

Wilson JL, Samaranayake VA, Limmer MA, Schumacher JG, Burken JG. Contaminant Gradients in Trees: Directional Tree Coring Reveals Boundaries of Soil and Soil-Gas Contamination with Potential Applications in Vapor Intrusion Assessment. Environ Sci Technol. 2017; 51(24), 14055-14064. doi: 10.1021/acs.est.7b03466. Epub 2017 Dec 8.

Wilson, J, Limmer, MA.,  Samaranayake, VA, Schumacher, J, Burken, J. Tree Sampling as a Method to Assess Vapor Intrusion Potential at a Site Characterized by VOC-Contaminated Groundwater and Soil. Environmental Science & Technology. 2017; 51(18), 10369–10378.

Ona, E., Long, S., and Samaranayake, VA. Mass deployment of sustainable transportation: evaluation of factors that influence electric vehicle adoption. Clean Technologies and Environment Policy. 2017; 19(7), 1927-1939. doi: 10.1007/s10098-017-1375-4.

Ray, CS, Samaranayake, VA,  Mohammadkhah, A, Day, TE, Day, DE. Iron phosphate glass waste forms for vitrifying Hanford AZ102 low activity waste (LAW), part I: Glass formation model. Journal of Non-Crystalline Solids. 2017; <http://dx.doi.org/10.1016/j.jnoncrysol.2016.11.019>

Anandan S, Dhaliwal G, Samaranayake VA, Chandrashekhara K, Fitzinger DP. Influence Of Cure Conditions On Out-Of-Autoclave Bismaleimide Composite Laminates. Journal of Applied Polymer Science. 2016; DOI: 10.1002/APP.43984

Zhong, X and Samaranayake, VA. Bootstrap-based Unit Root Tests for Higher Order Autoregressive Models with GARCH (1, 1) Errors. Journal of Statistical Computation and Simulation. 2016; 86(15), 3025-3037. DOI:10.1080/00949655.2016; 1146720.

Gosavi A, Daughton W, Senoz O, Samaranayake VA. Consumer Perception of U.S. and Japanese Automobiles: A Statistical Comparison via Consumer Reports and J.D. Power & Associates Data. International Journal of Engineering Management and Economics. 2016; 6(1), 1-18. Doi: 10.1504/IJEME.2016.079826

Zhong, X and Samaranayake, V.A., (2016). Bootstrap-based Unit Root Tests for Higher Order Autoregressive Models with GARCH (1, 1) Errors. Journal of Statistical Computation and Simulation. <http://www.tandfonline.com/doi/full/10.1080/00949655.2016.1146720 >.

Que S, Awuah-Offei K, Samaranayake V. A. (2015). Classifying critical factors that influence community acceptance of mining projects for discrete choice experiments in the United States. Journal of cleaner production. 87:489-500.

Mohammadi, Mojtaba A, Samaranayake, V.A., and Bham, Ghulam, H. (2014).Crash Frequency Modeling using Negative Binomial Models: An Application of Generalized Estimating Equation to    Longitudinal Data. Analytic Methods in Accident Research, 2, 52-69.

Dinesh Kanigolla, Elizabeth A. Cudney, Steven M. Corns, and Samaranayake V.A. (2014). Project Based Learning for Quality and Six Sigma Education. International Journal of Six Sigma and Competitive Advantage, 8(1), 51-68.

Rupasinghe, M., Mkhopadhyay, P., and Samaranayake, V.A. (2014). Obtaining Prediction Intervals for FARIMA processes using the Sieve bootstrap, Journal of Statistical Computation and Simulation, 84, No. 9, 2044-2058 .

Al Ghamari, A., Murry, Susan, and Samaranayake, V.A. (2013). The Effects of Wearing Respirators on Human Fine Motor, Visual, and Cognitive Performance, Ergonomics, 56(5), 791-802.

Rupasinghe, M. and Samaranayake, V.A. (2012). Asymptotic properties of sieve bootstrap prediction intervals for FARIMA processes, Statistics and Probability Letters, 82, 2108-2114

Butukuri, R.R., V.P., Bheemreddy, V.P., Chandrashekhara, K., and Samaranayake, V.A. (2012). Evaluation of low-velocity impact response of honeycomb sandwich structures using factorial-based design of Experiments, Journal of Sandwich Structures and Materials, 14: 339-361.

Mukhopadhyay, P. and Samaranayake, V.A. (2010). Prediction Intervals for Time Series: A Modified Sieve Bootstrap Approach, Communications in Statistics - Simulation and Computation, 39(03), 517 – 538.

Abstracts

Olbricht GR, Samaranayake VA, Injamuri S, Wang L, Fiebelman C, et al. (2014). Modeling Sleep and Wake Bouts in Drosophila Melanogaster. Annual Conference on Applied Statistics in Agriculture. Paper 4.

Thimgan, M.S., Injamuri, S. Fiebelman, C. Wang, L., Samaranayake, V.A., Olbricht. G. (2014). Relationship of sleep and wake bouts in Drosophila. Sleep, Abstract supplement, 37, A49.

Thimgan, M.S., Injamuri, S., Samaranayake, V.A., and Olbricht, G. (2013). Mathematical analysis of sleep and wake transitions in Drosophila melanogaster, Sleep Abstract supplement 36 A57.

Proceedings

Ekanayake, R. and Samaranayake, VA. Testing Unit Roots Using Artificial Neural Networks. In JSM Proceedings, Business and Economic Statistics Section, Section, Alexandria, VA, American Statistical Association. 2019; :1541 – 1550.

Ratnayake, I., and Samaranayake, VA. Modeling and Forecasting Financial Volatility Using Composite CARR Models. In JSM Proceedings, Business and Economic Statistics Section, Section, Alexandria, VA, American Statistical Association. 2019; :2805 – 2822.

Samaranayake, VA. And Zhang, Y. A periodic Conditional Poisson Model. In JSM Proceedings, Business and Economic Statistics Section, Section, Alexandria, VA, American Statistical Association. 2019; :2918 – 2935.

Krishnan, R., Jagannathan, S., and Samaranayake, VA. Deep learning inspired prognostics scheme for applications generating big data. Neural Networks (IJCNN), 2017 International Joint Conference on. IEEE, 2017. – Refereed.

Ratnayake, I., Samaranayake VA, A GARCH Type Poisson Model for Time Series of Counts with Cyclically Varying Zero Inflation. In JSM Proceedings, Business and Economic Statistics Section, Section, Alexandria, VA, American Statistical Association. 2017; :1760-1770.

Du, J., Samaranayake, VA. An Investigation of Conditional Heteroscedasticity Structural Change in S&P 500 Returns. In JSM Proceedings, Business and Economic Statistics Section, Section, Alexandria, VA, American Statistical Association. 2017; :1219-1227

Mohammadi,  AM, Samaranayake, VA,  and  Bham, G.H. Seasonal  Effects  of  Crash Contributing  Factors in  Highway  Safety, 94th Annual  Conference  of  the TRB, Washington, D.C., Jan. 2015.

Jayawardhana A, Samaranayake V.A. (2015). Lower Tolerance Bounds in Accelerated Life Testing for the Weibull Distribution. In JSM Proceedings, Quality and Productivity Section, Alexandria, VA, American Statistical Association. 2015; :1509-1516.

Eshebli A, Samaranayake V.A. (2015). Bootstrap-Based Confidence Intervals in Partially Accelerated Life Testing Under the Generalized Exponential Distribution. In JSM Proceedings, Quality and Productivity Section, Alexandria, VA, American Statistical Association. 873-883.

Samaranayake V. A, Liu J. (2015). An Investigation of the Day-of-the-Week Effect on the Volatility and Returns of Individual S&P 500 Sectors. In JSM Proceedings, Business and Economic Statistics Section, Alexandria, VA, American Statistical Association. 2991-3001.

Jornaz A, Samaranayake V.A.(2015). A Multi-step Approach to Modeling the 24-hour Daily Profiles of Electricity Load Using Seasonally-Varying Splines. In JSM Proceedings, Business and Economic Statistics Section. Alexandria, VA: American Statistical Association. 3785-3790.

Thilakaratne M, Rupasinghe M, Samaranayake V.A. (2014).Sieve Bootstrap-Based Prediction Intervals for Autoregressive Processes with GARCH Innovations. In JSM Proceedings, Business and Economic Statistics Section. Alexandria, VA: American Statistical Association. 3284-3296.

Zhong X, Samaranayake V.A. (2014). Bootstrap-Based Unit Root Tests for Higher Order Autoregressive Models with GARCH (1, 1) Errors. In In JSM Proceedings, Business and Economic StatisticsSection. Alexandria, VA: American Statistical Association. :3760-3769.

Jayawardhana A, Samaranayake V.A. (2014). Predictive Density Estimation in Accelerated Life Testing for Lognormal Life Distributions. In JSM Proceedings, Quality and Productivity Section. Alexandria, VA: American Statistical Association. 2325-2338.

Thilekaratne, M, and Samaranayake, V.A. (2013). Bootstrap-Based Prediction Intervals for conditional Heteroscedastic Models with Seasonnally Varying Unconditional Variance. ASA Proceedings of the Joint Statistical Meetings, American Statistical Association (Montreal, Canada),2967-2981.

Zhong, Xiao and Samaranayake, V.A. (2013). A Sieve Bootstrap-Based Test for Multiple Unit Roots. (2013). ASA Proceedings of the Joint Statistical Meetings, American Statistical Association (Montreal, Canada), 3312-3322.

Prediction Intervals for ARIMA Processes: Sieve Bootstrap Approach. (2012). ASA Proceedings of the Joint Statistical Meetings, American Statistical Association (Alexandria, VA),1078-1090

Rupasinghe, M. and Samaranayake, V.A. (2012). Obtaining Prediction Intervals for FARIMA Processes using the Sieve Bootstrap,Proceedings of the Joint Statistical Meetings, American Statistical Association, 3283-3293.

Alferink, A. and Samaranayake, V.A. (2011). Lifetime predictive Density Estimation in Accelerated Degradation Testing for Lognormal Response Distributions with Arrhenius Rate Relationship. Proceedings of the Joint Statistical Meetings, American Statistical Association, 4373-4385.